Abstract
This paper presents an efficient approach to achieve fast and accurate face detection in still gray level images. The structure of eye region is used as a robust cue to find possible eye pairs. Candidates of eye pair at different scales are discovered by finding regions which roughly match with the binary eye pair template. To obtain real ones, all the eye pair candidates are then verified by using SVM. Faces are finally located according to the eyes position. The proposed method is robust to deal with illumination changes, moderate rotations, glasses wearing and partial face occlusions. The proposed method is evaluated on the BioID face database. Comparative experimental results demonstrate its effectiveness.
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Wang, Q., Yang, W., Wang, H., Yang, J., Zheng, Y. (2006). Face Detection Using Binary Template Matching and SVM. In: Yang, Q., Webb, G. (eds) PRICAI 2006: Trends in Artificial Intelligence. PRICAI 2006. Lecture Notes in Computer Science(), vol 4099. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36668-3_168
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DOI: https://doi.org/10.1007/978-3-540-36668-3_168
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36667-6
Online ISBN: 978-3-540-36668-3
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